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Abstract P3-04-25: Role of <i>H19</i>, a long non-coding RNA, in development of resistance to endocrine therapy in breast cancer cells

2017· article· en· W2592575712 on OpenAlexaff
Pratima Basak, Sanjoy Chatterjee, Vinay Bhat, Hong Jin, Amber Su, Leigh C. Murphy, Afshin Raouf

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsUniversity of ManitobaResearch Institute in Oncology and Hematology
Fundersnot available
KeywordsGene knockdownCancer researchBreast cancerEstrogen receptorEstrogenEndocrine systemCancerAntiestrogenMedicineInternal medicineBiologyEndocrinologyCell cultureHormoneGenetics

Abstract

fetched live from OpenAlex

Abstract Introduction: Majority of breast cancer tumors are Estrogen receptor positive (ER+) where antiestrogen therapies (endocrine therapies) are the best therapeutic strategy to treat this type of tumors. However, eventually over 30% of patients will develop resistance to endocrine therapies resulting in disease relapse. We recently showed that the long noncoding RNA, H19, is an estrogen target gene that plays a significant role in estrogen-induced proliferation of the normal and malignant ER+ cells. We therefore hypothesize that H19 expression is also important to the proliferation of endocrine therapy resistant cells. In this study, we examined if estrogen-independent H19 expression is important to the development of endocrine therapy resistance. Objective: The overall objective of this project is to use therapy sensitive (MCF-7) and therapy-resistant (LCC9) breast cancer cells as model systems to examine the role of long non-coding RNA H19 in development and maintenance of resistance to endocrine therapy. Methodology and Results: We examined the expression of H19 in ER+ breast cancer cells (MCF7) that under the selective pressure of fulvesterant (ICI, ER down regulator) acquire resistance to ICI. We observed that while H19 expression was initially decreased as expected, its expression subsequently increased in the ICI-resistant MCF7 cells. Interestingly, H19 knockdown in MCF7 cells significantly decrease their proliferation as determined by Flowcytometry and made them more sensitive to ICI. We also examined H19 expression in the ICI-resistant LCC9 cells and found that ICI treatment increased H19 expression. Interestingly, H19 knockdown in the LCC9 cells decreased their proliferation and surprisingly made them sensitive to ICI treatment. Previous observations indicate that NOTCH4 receptor (NR4) may be involved in endocrine therapy resistance. Interestingly we found that in presence of ICI, NR4 expression is increased and that forced activation of NR4 markedly increases H19 expression in LCC9 cells. Conclusion: Altogether these observations suggest that H19 plays an important role in the development of endocrine therapy resistance and further our understanding of the cellular and molecular mechanisms involved in endocrine therapy resistance. These and similar studies could potentially lead to the development of new therapies to treat therapy resistant tumor cells. Further experiments would reveal if signalling pathways that regulate H19 expression independent of estrogen are useful therapies against endocrine therapy resistant tumors. Citation Format: Basak P, Chatterjee S, Bhat V, Jin H, Su A, Murphy LC, Raouf A. Role of H19, a long non-coding RNA, in development of resistance to endocrine therapy in breast cancer cells [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P3-04-25.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.372
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2017
Admission routes1
Has abstractyes

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